Update app.py

app.py

@@ -48,7 +48,7 @@ def main():
                 st.write(total_late_interest)
 
             # Generate conversation prompt
-            prompt = generate_conversation_prompt(df)
+            prompt = generate_conversation_prompt(df, boe_rates_df)
 
             # Allow user to engage in conversation
             user_input = st.text_input("Start a conversation:")
@@ -66,36 +66,48 @@ def main():
                 response = completion.choices[0].message['content']
                 st.write("AI's Response:")
                 st.write(response)
-
-        # Button to clear cache
-        if st.button("Clear Cache"):
-            st.cache.clear()
-
     else:
         st.warning("Please enter your OpenAI API key.")
 
-# Function to calculate late interest
+# Function to generate conversation prompt
+def generate_conversation_prompt(df, boe_rates_df):
+    prompt = "I have analyzed the provided Excel sheet. "
+
+    # Include due dates, payment dates, and amounts from the Excel sheet
+    due_dates = df['due_date'].tolist()
+    payment_dates = df['payment_date'].tolist()
+    amounts = df['amount'].tolist()
+    prompt += f"The due dates in the sheet are: {', '.join(str(date) for date in due_dates)}. "
+    prompt += f"The payment dates in the sheet are: {', '.join(str(date) for date in payment_dates)}. "
+    prompt += f"The amounts in the sheet are: {', '.join(str(amount) for amount in amounts)}. "
+
+    # Include Bank of England base rates
+    if boe_rates_df is not None:
+        prompt += "The Bank of England base rates are as follows: \n"
+        for index, row in boe_rates_df.iterrows():
+            prompt += f"On {row['Date Changed']}, the base rate was {row['Current Bank Rate']}. \n"
+
+    prompt += "Based on this information, what would you like to discuss?"
+
+    return prompt
 
+# Function to calculate late interest
 def calculate_late_interest(data, late_interest_rate, boe_rates_df):
     # Convert due_date column to Timestamp objects
     data['due_date'] = pd.to_datetime(data['due_date'])
+    data['payment_date'] = pd.to_datetime(data['payment_date'])
 
     # Calculate late days and late interest
     data['late_days'] = (data['payment_date'] - data['due_date']).dt.days.clip(lower=0)
     data['late_interest'] = data['late_days'] * data['amount'] * (late_interest_rate / 100)
 
     # Consider additional factors like Bank of England base rate
-    data['boe_base_rate'] = data['due_date'].map(lambda x: get_boe_base_rate(x, boe_rates_df))
-    data['late_interest'] += data['amount'] * (data['boe_base_rate'] / 100)
+    if boe_rates_df is not None:
+        data['boe_base_rate'] = data['due_date'].map(lambda x: get_boe_base_rate(x, boe_rates_df))
+        data['late_interest'] += data['amount'] * (data['boe_base_rate'] / 100)
 
     return data
 
-
-# Function to get Bank of England base rate for a given date
-def get_boe_base_rate(date, boe_rates_df):
-    closest_date = boe_rates_df['Date Changed'].iloc[(boe_rates_df['Date Changed']-date).abs().argsort()[0]]
-    return boe_rates_df[boe_rates_df['Date Changed'] == closest_date]['Base Rate'].values[0]
-
 # Function to analyze Excel sheet and extract relevant information
 def analyze_excel(df):
     # Extract due dates and payment dates
@@ -132,18 +144,10 @@ def download_boe_rates():
         st.error(f"Failed to download rates: {e}")
         return None
 
-# Function to generate conversation prompt
-def generate_conversation_prompt(df):
-    prompt = "I have analyzed the provided Excel sheet. "
-    due_dates, payment_dates, amounts = analyze_excel(df)
-    if due_dates:
-        prompt += f"The due dates in the sheet are: {', '.join(str(date) for date in due_dates)}. "
-    if payment_dates:
-        prompt += f"The payment dates in the sheet are: {', '.join(str(date) for date in payment_dates)}. "
-    if amounts:
-        prompt += f"The amounts in the sheet are: {', '.join(str(amount) for amount in amounts)}. "
-    prompt += "Based on this information, what would you like to discuss?"
-    return prompt
+# Function to get Bank of England base rate for a given date
+def get_boe_base_rate(date, boe_rates_df):
+    closest_date = boe_rates_df['Date Changed'].iloc[(boe_rates_df['Date Changed'] - date).abs().argsort()[0]]
+    return boe_rates_df.loc[boe_rates_df['Date Changed'] == closest_date, 'Current Bank Rate'].values[0]
 
 if __name__ == "__main__":
     main()